Pub Date : 2025-08-05DOI: 10.1016/j.sbi.2025.103126
Tanaya Basu Roy , Mana Heidari , Nikolay V. Dokholyan
Optogenetically regulated enzymes offer unprecedented spatiotemporal control over protein activity, intermolecular interactions, and intracellular signaling. Many design strategies have been developed for their fabrication based on the principles of intrinsic allostery, oligomerization or ‘split’ status, intracellular compartmentalization, and steric hindrance. In addition to employing photosensory domains as part of the traditional optogenetic toolset, the specificity of effector domains has also been leveraged for endogenous applications. Here, we discuss the dynamics of light activation while providing a bird's eye view of the crafting approaches, targets, and impact of optogenetic enzymes in orchestrating cellular functions, as well as the bottlenecks and an outlook into the future.
{"title":"Optogenetic enzymes: A deep dive into design and impact","authors":"Tanaya Basu Roy , Mana Heidari , Nikolay V. Dokholyan","doi":"10.1016/j.sbi.2025.103126","DOIUrl":"10.1016/j.sbi.2025.103126","url":null,"abstract":"<div><div>Optogenetically regulated enzymes offer unprecedented spatiotemporal control over protein activity, intermolecular interactions, and intracellular signaling. Many design strategies have been developed for their fabrication based on the principles of intrinsic allostery, oligomerization or ‘split’ status, intracellular compartmentalization, and steric hindrance. In addition to employing photosensory domains as part of the traditional optogenetic toolset, the specificity of effector domains has also been leveraged for endogenous applications. Here, we discuss the dynamics of light activation while providing a bird's eye view of the crafting approaches, targets, and impact of optogenetic enzymes in orchestrating cellular functions, as well as the bottlenecks and an outlook into the future.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"94 ","pages":"Article 103126"},"PeriodicalIF":6.1,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144781330","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-08-04DOI: 10.1016/j.sbi.2025.103125
Virgil A. Woods , Shivani Sharma , Alexis M. Lemberikman , Daniel A. Keedy
Protein tyrosine phosphatases (PTPs) are a family of enzymes that play critical roles in intracellular signaling and regulation. PTPs are conformationally dynamic, exhibiting motions of catalytic loops and additional regions of the structurally conserved catalytic domain. However, many questions remain about how dynamics contribute to catalysis and allostery in PTPs, how these behaviors vary among evolutionarily divergent PTP family members, and how mutations and ligands reshape dynamics to modulate PTP function. Recently, our understanding in these areas has expanded significantly, thanks to novel applications of existing methods and emergence of new approaches in structural biology and biophysics. Here we review exciting advances in this realm from the last few years. We organize our commentary both by experimental and computational methodologies, including solution techniques, avant-garde crystallography, molecular dynamics simulations, and bioinformatics, and also by scientific focus, including regulatory mechanisms, mutations and protein engineering, and small-molecule ligands such as allosteric modulators.
{"title":"Orchestrating function: Concerted dynamics, allostery, and catalysis in protein tyrosine phosphatases","authors":"Virgil A. Woods , Shivani Sharma , Alexis M. Lemberikman , Daniel A. Keedy","doi":"10.1016/j.sbi.2025.103125","DOIUrl":"10.1016/j.sbi.2025.103125","url":null,"abstract":"<div><div>Protein tyrosine phosphatases (PTPs) are a family of enzymes that play critical roles in intracellular signaling and regulation. PTPs are conformationally dynamic, exhibiting motions of catalytic loops and additional regions of the structurally conserved catalytic domain. However, many questions remain about how dynamics contribute to catalysis and allostery in PTPs, how these behaviors vary among evolutionarily divergent PTP family members, and how mutations and ligands reshape dynamics to modulate PTP function. Recently, our understanding in these areas has expanded significantly, thanks to novel applications of existing methods and emergence of new approaches in structural biology and biophysics. Here we review exciting advances in this realm from the last few years. We organize our commentary both by experimental and computational methodologies, including solution techniques, avant-garde crystallography, molecular dynamics simulations, and bioinformatics, and also by scientific focus, including regulatory mechanisms, mutations and protein engineering, and small-molecule ligands such as allosteric modulators.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"94 ","pages":"Article 103125"},"PeriodicalIF":6.1,"publicationDate":"2025-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144768528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-31DOI: 10.1016/j.sbi.2025.103128
Anand Srivastava
Since the publication of the first papers in the early 1990s, molecular simulation as a reliable biophysical tool in the area of membrane biophysics has come a long way. Advances in simulation algorithms, coupled with exascale computing have pushed the size and time scales of biomolecular membrane simulations to scales where connections to experiments are made with higher fidelity. When integrated with experimental data in a theoretically well-grounded manner, current biomolecular simulations are providing indispensable insights that cannot be obtained through experiments alone. Here, I summarize some recent developments where simulations have allowed a deeper understanding in membrane spatiotemporal organization. I also discuss the need for transformative method developments to meet recent breakthroughs in experimental measurements at molecular scales.
{"title":"Emerging paradigms in the lateral and transverse organization in biological membrane and their functional implications: Connecting the dots with biomolecular simulations","authors":"Anand Srivastava","doi":"10.1016/j.sbi.2025.103128","DOIUrl":"10.1016/j.sbi.2025.103128","url":null,"abstract":"<div><div>Since the publication of the first papers in the early 1990s, molecular simulation as a reliable biophysical tool in the area of membrane biophysics has come a long way. Advances in simulation algorithms, coupled with exascale computing have pushed the size and time scales of biomolecular membrane simulations to scales where connections to experiments are made with higher fidelity. When integrated with experimental data in a theoretically well-grounded manner, current biomolecular simulations are providing indispensable insights that cannot be obtained through experiments alone. Here, I summarize some recent developments where simulations have allowed a deeper understanding in membrane spatiotemporal organization. I also discuss the need for transformative method developments to meet recent breakthroughs in experimental measurements at molecular scales.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"94 ","pages":"Article 103128"},"PeriodicalIF":6.1,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144739059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-30DOI: 10.1016/j.sbi.2025.103123
Yuan He, Yawen Bai
{"title":"Editorial overview of 3D genome chromatin organization and regulation","authors":"Yuan He, Yawen Bai","doi":"10.1016/j.sbi.2025.103123","DOIUrl":"10.1016/j.sbi.2025.103123","url":null,"abstract":"","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"94 ","pages":"Article 103123"},"PeriodicalIF":6.1,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144724691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-29DOI: 10.1016/j.sbi.2025.103124
Qiang Cui
Major progress has been made in recent years in terms of strategies for regulating enzyme activities. Novel high-throughput enzyme kinetic assays and efficient computational methodologies enabled a deeper understanding of molecular mechanisms that dictate the activity of enzymes, which provide guidance to rational modulation of enzyme catalysis. Continued development of efficient screening, directed evolution technologies, and machine learning–driven protein engineering tools make it possible to tune enzyme activities without having to understand the detailed mechanism of catalysis regulation. By combining these two limiting approaches, the efficiency of enzyme regulation can be substantially improved as a mechanistic understanding can help reduce the size of design space before the ‘brute-force’ engineering approach takes over. We briefly discuss relevant advances in both experiment and computation and comment on future developments that can further enhance mechanistic understanding and engineering capability for broad applications.
{"title":"Approaches for regulating enzyme activities: Recent advances in experiment and computation","authors":"Qiang Cui","doi":"10.1016/j.sbi.2025.103124","DOIUrl":"10.1016/j.sbi.2025.103124","url":null,"abstract":"<div><div>Major progress has been made in recent years in terms of strategies for regulating enzyme activities. Novel high-throughput enzyme kinetic assays and efficient computational methodologies enabled a deeper understanding of molecular mechanisms that dictate the activity of enzymes, which provide guidance to rational modulation of enzyme catalysis. Continued development of efficient screening, directed evolution technologies, and machine learning–driven protein engineering tools make it possible to tune enzyme activities without having to understand the detailed mechanism of catalysis regulation. By combining these two limiting approaches, the efficiency of enzyme regulation can be substantially improved as a mechanistic understanding can help reduce the size of design space before the ‘brute-force’ engineering approach takes over. We briefly discuss relevant advances in both experiment and computation and comment on future developments that can further enhance mechanistic understanding and engineering capability for broad applications.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"94 ","pages":"Article 103124"},"PeriodicalIF":6.1,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144724690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-17DOI: 10.1016/j.sbi.2025.103119
Chun Kit Chan , Christine Rajarigam , Patrick Jiang , Jacob Miratsky , Mustafa Demir , Melih Sener , Abhishek Singharoy
It has been a longstanding dream of the structural biology and molecular biophysics communities to determine protein functions directly from the amino acid sequences. Most methods available today, however, are homology- or library-based and often undermine determining divergent functions from comparable sequences or vice versa. The sequence-to-function relationship is intrinsically dependent on the biophysical space of protein dynamics, which can be potentially exploited to annotate function. But, despite three decades of active research, the space of molecular dynamics data remains grossly underpopulated. By employing surveys of the existing literature, we highlight this gray area in the context of machine learning methods. Thereafter, we share examples that point toward learning biophysical representations—or signatures—and combining them with integrative models as means to robustly associate sequence with function. The aim is to avoid having to compute protein dynamics for an impossible thousand years to achieve data completeness and generalization.
{"title":"A to-do list for realizing the sequence-to-function paradigm of proteins","authors":"Chun Kit Chan , Christine Rajarigam , Patrick Jiang , Jacob Miratsky , Mustafa Demir , Melih Sener , Abhishek Singharoy","doi":"10.1016/j.sbi.2025.103119","DOIUrl":"10.1016/j.sbi.2025.103119","url":null,"abstract":"<div><div>It has been a longstanding dream of the structural biology and molecular biophysics communities to determine protein functions directly from the amino acid sequences. Most methods available today, however, are homology- or library-based and often undermine determining divergent functions from comparable sequences or vice versa. The sequence-to-function relationship is intrinsically dependent on the biophysical space of protein dynamics, which can be potentially exploited to annotate function. But, despite three decades of active research, the space of molecular dynamics data remains grossly underpopulated. By employing surveys of the existing literature, we highlight this gray area in the context of machine learning methods. Thereafter, we share examples that point toward learning biophysical representations—or signatures—and combining them with integrative models as means to robustly associate sequence with function. The aim is to avoid having to compute protein dynamics for an impossible thousand years to achieve data completeness and generalization.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"93 ","pages":"Article 103119"},"PeriodicalIF":6.1,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144657182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-14DOI: 10.1016/j.sbi.2025.103117
Ecenaz Bilgen, Don C. Lamb
Förster resonance energy transfer (FRET) is a powerful tool for studying protein conformations, interactions, and dynamics at the single-molecule level. Multicolor FRET extends conventional two-color FRET by incorporating three or more fluorophores and thereby enabling a more comprehensive view of complex biomolecular processes. This technique allows for the simultaneous tracking of multiple structural changes, detecting intermediate states, and resolving heterogeneous population distributions. In this review, we discuss the recent advancements in fluorophore labeling strategies and data analysis methods that have significantly improved the precision and applicability of multicolor FRET in protein studies. We then end this review by showcasing recent applications for investigating protein folding and processes involved in gene regulation.
{"title":"Multicolor single-molecule FRET studies on dynamic protein systems","authors":"Ecenaz Bilgen, Don C. Lamb","doi":"10.1016/j.sbi.2025.103117","DOIUrl":"10.1016/j.sbi.2025.103117","url":null,"abstract":"<div><div>Förster resonance energy transfer (FRET) is a powerful tool for studying protein conformations, interactions, and dynamics at the single-molecule level. Multicolor FRET extends conventional two-color FRET by incorporating three or more fluorophores and thereby enabling a more comprehensive view of complex biomolecular processes. This technique allows for the simultaneous tracking of multiple structural changes, detecting intermediate states, and resolving heterogeneous population distributions. In this review, we discuss the recent advancements in fluorophore labeling strategies and data analysis methods that have significantly improved the precision and applicability of multicolor FRET in protein studies. We then end this review by showcasing recent applications for investigating protein folding and processes involved in gene regulation.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"93 ","pages":"Article 103117"},"PeriodicalIF":6.1,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144631193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-14DOI: 10.1016/j.sbi.2025.103120
Pin Yu Chew , Rosana Collepardo-Guevara
Biomolecular condensates play crucial roles in cellular organisation, regulating diverse biological functions as well as contributing to disease pathologies when phase separation is dysregulated. Computer simulations and theoretical approaches have emerged as powerful tools to probe the molecular mechanisms governing phase transitions in these systems. This review highlights recent advancements in computational methods, focusing on coarse-grained and all-atom molecular dynamics simulations, to elucidate the driving forces underlying protein and RNA condensate formation and how their stability and material properties can be regulated and tuned. Additionally, we address new strategies for designing synthetic condensates with tunable properties and leveraging predictive models to guide experimental studies. The integration of molecular simulations, with data-driven approaches and theory, has expanded our understanding of biomolecular condensates, offering novel insights into both fundamental biology and physics, as well as potential practical applications.
{"title":"Probing molecular and biophysical mechanisms of RNA and protein phase transitions with simulations and theory","authors":"Pin Yu Chew , Rosana Collepardo-Guevara","doi":"10.1016/j.sbi.2025.103120","DOIUrl":"10.1016/j.sbi.2025.103120","url":null,"abstract":"<div><div>Biomolecular condensates play crucial roles in cellular organisation, regulating diverse biological functions as well as contributing to disease pathologies when phase separation is dysregulated. Computer simulations and theoretical approaches have emerged as powerful tools to probe the molecular mechanisms governing phase transitions in these systems. This review highlights recent advancements in computational methods, focusing on coarse-grained and all-atom molecular dynamics simulations, to elucidate the driving forces underlying protein and RNA condensate formation and how their stability and material properties can be regulated and tuned. Additionally, we address new strategies for designing synthetic condensates with tunable properties and leveraging predictive models to guide experimental studies. The integration of molecular simulations, with data-driven approaches and theory, has expanded our understanding of biomolecular condensates, offering novel insights into both fundamental biology and physics, as well as potential practical applications.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"93 ","pages":"Article 103120"},"PeriodicalIF":6.1,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144614740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-10DOI: 10.1016/j.sbi.2025.103118
Eliza Gazaway , Rajan Kandel , Oliver C. Grant, Robert J. Woods
The covalent attachment of oligosaccharides to asparagine side chains on protein surfaces (N-linked glycosylation) is a ubiquitous modification that is critical to protein stability and function. Experimental 3D structures of glycoproteins in which the N-linked glycans are well resolved are rare due to both the presumed flexibility of the N-linked glycan and to glycan microheterogeneity. To surmount these limitations, computational modeling is often applied to glycoproteins, particularly to generate an ensemble of 3D shapes for the N-linked glycans. While the number of glycoprotein modelling tools continues to expand, the available experimental data against which the predictions can be validated remains extremely limited. Here, we present our current understanding of the dynamic properties of N-linked glycans, with a particular focus on features that impact their presentation (orientation) relative to the protein surface. Additionally, we review the limits of experimental and theoretical studies of glycoproteins, and ask the question, “Are N-linked glycans intrinsically disordered?”.
{"title":"Are N-linked glycans intrinsically disordered?","authors":"Eliza Gazaway , Rajan Kandel , Oliver C. Grant, Robert J. Woods","doi":"10.1016/j.sbi.2025.103118","DOIUrl":"10.1016/j.sbi.2025.103118","url":null,"abstract":"<div><div>The covalent attachment of oligosaccharides to asparagine side chains on protein surfaces (<em>N-</em>linked glycosylation) is a ubiquitous modification that is critical to protein stability and function. Experimental 3D structures of glycoproteins in which the <em>N-</em>linked glycans are well resolved are rare due to both the presumed flexibility of the <em>N-</em>linked glycan and to glycan microheterogeneity. To surmount these limitations, computational modeling is often applied to glycoproteins, particularly to generate an ensemble of 3D shapes for the <em>N-</em>linked glycans. While the number of glycoprotein modelling tools continues to expand, the available experimental data against which the predictions can be validated remains extremely limited. Here, we present our current understanding of the dynamic properties of <em>N-</em>linked glycans, with a particular focus on features that impact their presentation (orientation) relative to the protein surface. Additionally, we review the limits of experimental and theoretical studies of glycoproteins, and ask the question, “Are <em>N-</em>linked glycans intrinsically disordered?”.</div></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"93 ","pages":"Article 103118"},"PeriodicalIF":6.1,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144595750","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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